The present invention is generally related to forward path geometry estimation, and more specifically to a method and apparatus for accurate estimation of forward path geometry of a vehicle based on a two-clothoid road model.
Vehicular land and road detection systems have been the subject of significant research. Applications such as adaptive cruise control, collision avoidance systems, and vehicle guidance systems require knowledge of the geometry of the road to be most effective. It is difficult for a collision avoidance system to accurately characterize a stationary or slower moving object as non-hazardous unless there is some certainty that the stationary object is not in the vehicle""s path. Previous approaches to estimation of forward road geometry, model the road in the forward view as either a constant curvature or a linearly varying curvature. These road geometry estimation approaches then fit parameters of these models via a least-squares fitting technique or other mathematical technique. The linearly varying curvature model is usually referred to as a single-clothoid model and is completely described by two coefficients, c0, the local curvature at host vehicle position and c1 the rate of change of curvature with distance. Both the constant curvature and single-clothoid road models do not adequately represent road geometry, especially when there are abrupt changes in curvature in the look-ahead range. Such sharp changes in curvature are common on many roads. This is also seen on many freeways, where a straightaway section transitions to a curved section abruptly and vice-versa. Thus, methods based on these simple models are generally inaccurate in adequately describing forward road geometry.
To overcome the problem of inaccurate road geometry estimation with these simple models, an averaged curvature road model was proposed. This approach works well on roads with low curvature and very smooth curvature changes, but still fails on roads with significant curvature changes or discontinuities in c1. To reduce these errors further, more complex road models were proposed that split the road into multiple clothoid segments. The transition between segments is estimated using ad-hoc methods such as the generalized likelihood ratio test. In this approach, the geometry of the segments is not dynamic and is updated using measurements that fall in the corresponding segment. A dynamic model is required for vehicle dynamics only, as the road model remains spatially fixed, while the vehicle is moving through the road segments. One of the fundamental limitations of this approach is that road geometry estimation accuracy is strongly dependent on reliable detection of transition points between segments making it very sensitive to noise in the measurements. Thus they are often inaccurate in moderate and high noise measurement conditions. In addition, the segmentation process is computationally expensive because the likelihood ratio test has to be performed for each new measurement.
A naxc3xafve approach of using a road model based on a higher-order polynomial to solve these problems with previous methods will lead to over-fitting road geometry and a statistically insignificant estimate of the coefficient of this higher order term. This will also make this approach more sensitive to noise. Thus, it would be desirable to develop a model that overcomes the problems associated with previous approaches. Ideally such a model would be simple to implement and would not as computationally intensive or ad-hoc as the previous multi-clothoid models.
The present invention provides a method and apparatus for accurate estimation of the forward path geometry of a vehicle based on a two-clothoid road model. The primary components of the invention include a data collection element configured to provide collected data to a first processing element. The data collection element could be a camera sensitive to signals in the visible or infrared region or a combination thereof. Alternatively the data collection element might be a radar transceiver used alone or in conjunction with a camera. The first processing element computes a full measurement transfer function of a two-clothoid road model and conveys the full measurement transfer function to a second processing element. In one embodiment the processing elements in this invention are preprogrammed computers. The processing elements could also include application specific integrated circuits, or devices configured to respond to internal or external instructions. The second processing element is configured to utilize the full measurement transfer function to simultaneously estimate the near-range clothoid coefficients and far-range clothoid coefficients, a third processing element then combines the near-range clothoid coefficients and far-range clothoid coefficients to provide a forward path description.